Radiology

Nuclear Medicine

Latest AI and machine learning research in nuclear medicine for healthcare professionals.

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CT-Less Whole-Body Bone Segmentation of PET Images Using a Multimodal Deep Learning Network.

In bone cancer imaging, positron emission tomography (PET) is ideal for the diagnosis and staging of...

Diffused Multi-scale Generative Adversarial Network for low-dose PET images reconstruction.

PURPOSE: The aim of this study is to convert low-dose PET (L-PET) images to full-dose PET (F-PET) im...

Evaluation of deep learning-based scatter correction on a long-axial field-of-view PET scanner.

OBJECTIVE: Long-axial field-of-view (LAFOV) positron emission tomography (PET) systems allow higher ...

Optimizing MR-based attenuation correction in hybrid PET/MR using deep learning: validation with a flatbed insert and consistent patient positioning.

PURPOSE: To address the challenges of verifying MR-based attenuation correction (MRAC) in PET/MR due...

Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach.

BACKGROUND: Computed tomography attenuation correction (CTAC) is commonly used in cardiac SPECT imag...

The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update.

This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in...

Integrating deep learning algorithms for forecasting evapotranspiration and assessing crop water stress in agricultural water management.

The increasing impacts of climate change on global agriculture necessitate the development of advanc...

Self-supervised parametric map estimation for multiplexed PET with a deep image prior.

Multiplexed positron emission tomography (mPET) imaging allows simultaneous observation of physiolog...

Deep Learning-Based Precontrast CT Parcellation for MRI-Free Brain Amyloid PET Quantification.

PURPOSE: This study aimed to develop a deep learning (DL) model for brain region parcellation using ...

Deep Learning-Powered CT-Less Multitracer Organ Segmentation From PET Images: A Solution for Unreliable CT Segmentation in PET/CT Imaging.

PURPOSE: The common approach for organ segmentation in hybrid imaging relies on coregistered CT (CTA...

Continuous single-ended depth-of-interaction measurement using highly multiplexed signals and artificial neural networks.

. This study aims to enhance positron emission tomography (PET) imaging systems by developing a cont...

Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.

Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection ...

Empowering PET imaging reporting with retrieval-augmented large language models and reading reports database: a pilot single center study.

PURPOSE: The potential of Large Language Models (LLMs) in enhancing a variety of natural language ta...

Clinical impact of an explainable machine learning with amino acid PET imaging: application to the diagnosis of aggressive glioma.

PURPOSE: Radiomics-based machine learning (ML) models of amino acid positron emission tomography (PE...

Artificial intelligence applied in identifying left ventricular walls in myocardial perfusion scintigraphy images: Pilot study.

This paper proposes the use of artificial intelligence techniques, specifically the nnU-Net convolut...

Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.

Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often un...

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